Chemicals, biological materials and particulates are continuously released into the atmosphere and water supply. Major spills are obvious and are immediately remediated. What is unknown is how many sub ppm contaminations the public is inundated with on a daily basis and how these low level contaminations affect community health over time. The NIEHS seeks to establish large scale long-term biomonitoring programs to accurately determine current contamination issues and develop models to predict long term health implications. To amass the enormous amount of data in this undertaking, fieldable devices will be developed to rapidly provide the desired information with high levels of precision. The data collection has to be very inexpensive per measurement or the undertaking will fail from cost issues alone. In this program, we are developing an inexpensive Surface-Enhanced Raman Spectroscopy (SERS) reader to monitor contaminants in the vapor and aqueous phases. Our preliminary demonstration is for the detection of pesticides in the air surrounding farmworkers during harvesting seasons and on surfaces of farmworker dwellings, and of pesticide metabolites in farmworker urine samples. In the Phase I program, we successfully demonstrated that pesticides in the vapor phase could be detected at CDC relevant concentrations and that pesticide metabolites could be detected in synthetic and real urine samples at biologically relevant concentrations. In the Phase II program, a high resolution automated SERS reader will be taken into the field for pesticide analysis. SERS vapor spectra and urinalyses will be collected in the 2011 and 2012 harvesting seasons. Precision, accuracy and cost effectiveness will all be demonstrated. The Phase II results will allow the SERS reader to transition into other pesticide analysis programs as well as progress to other biomonitoring programs of relevance to the NIEHS. PUBLIC HEALTH RELEVANCE: This project will allow NIEHS and other monitoring agencies of public health to define long-term health effects of low pesticide levels on the population as a whole. The sensors developed will allow for a direct correlation between external pesticide concentrations a person is exposed to and the actual ingested concentration, measured as metabolites in urine. The sensor developed herein can be used for all pesticides/crops and can be modified to monitor other environmental contaminants as well.